CFP last date
20 December 2024
Reseach Article

Geometry Compression for 3D Polygonal Models using a Neural Network

by Nadine Abu Rumman, Samir Abou El-Seoud, Khalaf F. Khatatneh, Christain Gutl
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 29
Year of Publication: 2010
Authors: Nadine Abu Rumman, Samir Abou El-Seoud, Khalaf F. Khatatneh, Christain Gutl
10.5120/580-744

Nadine Abu Rumman, Samir Abou El-Seoud, Khalaf F. Khatatneh, Christain Gutl . Geometry Compression for 3D Polygonal Models using a Neural Network. International Journal of Computer Applications. 1, 29 ( February 2010), 13-22. DOI=10.5120/580-744

@article{ 10.5120/580-744,
author = { Nadine Abu Rumman, Samir Abou El-Seoud, Khalaf F. Khatatneh, Christain Gutl },
title = { Geometry Compression for 3D Polygonal Models using a Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 29 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 13-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number29/580-744/ },
doi = { 10.5120/580-744 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:41:57.654892+05:30
%A Nadine Abu Rumman
%A Samir Abou El-Seoud
%A Khalaf F. Khatatneh
%A Christain Gutl
%T Geometry Compression for 3D Polygonal Models using a Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 29
%P 13-22
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Three dimensional models are commonly used in computer graphics and 3D modeling characters in animation movies and games. 3D objects are more complex to handle than other multimedia data due to the fact that various representations exist for the same object, yielding a number of difficulties, among of which are the distinct sources of 3D data. Research work in the field of three dimensional environments is represented by a broad spectrum of applications. In this paper we restrict ourselves only on how to do compression using a neural network in order to minimize the size of 3D models for making transmission over networks much faster. The main objective behind this compression is to simplify the 3D model and make handling the large size of 3d objects much easier for other processes. Even the process of rendering, digital watermarking, etc., will be faster and more efficient.

References
  1. . M. Isenburg and J. Snoeyink, " Face Fixer Compressing Polygon Meshes with Properties" , ACM Siggraph Conference Proc, pp. 263-270,2001.
  2. . 3D Object Processing: Compression, Indexing and Watermarking. Edited by J.-L. Dugelay, A. Baskurt and M. Daoudi, John Wiley & Sons, Ltd. ISBN: 978-0-470-06542-6, 2008.
  3. . H. Donald and M. Pauline Barker. 1996, Computer Graphics, C Version (2nd Edition), Publisher: Prentice Hall: ISBN-13: 978-0135309247.
  4. . A. M. Chang, and L. O. Hall 1992, The validation of fuzzy knowledge-based systems, Fuzzy Logic for the Management of Uncertainty, L.A. Zadeh and J. Kacprzyk, eds, John Wiley, New York, pp. 589-604.
  5. . M.Deering. 1995, Geometry compression. ACM SIGGRAPH, pp. 13–20
  6. . M. Isenburg, S.Gumhold. 2003, Out-of-core compression for gigantic polygon meshes. ACM Trans. Graph. 22(3): 935-942.
  7. . M. Isenburg, P. Alliez. 2002, Compressing Polygon Mesh Geometry with Parallelogram Prediction, in Proceedings of Visualization 2002, pages 141-146.
  8. . Z.Karni and C.Gotsman. 2000, Spectral compression of mesh geometry, ACM SIGGRAPH, pp. 279–286.
  9. . D.Luebke and B.Hallen. 2001, Perceptually driven simplification for interactive rendering. Eurographics Workshop on Rendering Techniques, pp. 223–234.
  10. . M.Chow, Optimizel geometry compression for real-time rendering, In Proceedinngs of IEEE Visualization '97, Phowenix AZ, pp. 347-354, 1997
  11. . J. Rossignac. Edgebreaker: Connectivity compression for triangle meshes. IEEE Transactions on Visualization and Computer Graphics, 5(1), 1999.
  12. . D. King, J. Rossignac, and A. Szymczak. 1999, Connectivity compression for irregular quadrilateral meshes, Technical Report TR–99–36, GVU, Georgia Tech.
  13. . A.Khodakovsky, P.Alliez, M. Desbrun and P.Schröder. 2002, Near-Optimal Connectivity Encoding of 2-Manifold Polygon Meshes. Graphical Models 64(3-4): 147-168.
  14. . E. Piperakis, I. Kumazawa. 2001,3D Polygon Mesh Compression with Multi Layer Feed Forward Neural Networks, SYSTEMICS, CYBERNETICS AND INFORMATICS VOLUME 1 - NUMBER 3.
  15. . S. Haykin. 1994, Neural Networks, A Comprehensive Foundation. Macmillan College Publishing Company.
  16. . P.Maheshwari, P.Agarwal, and B. Prabhakaran. 2007, Progressive compression invariant semi-fragile watermarks for 3D meshes, in Proceedings of ACM Multimedia and Security Workshop 2007 (MM&Sec 2007), Dallas , TX , USA , pp. 245-25.
  17. . D.Luebke and B.Hallen. 2001, Perceptually driven simplification for interactive rendering. Eurographics Workshop on Rendering Techniques, pp. 223–234.
  18. . Cox, M. Miller, J.Bloom. 2001 , Digital Watermarking: Principle & Practice ( The Morgan Series im Multimedia and Information Systems), ISBN-1558607145.
  19. . R.Ohbuchi, M.Nakazawa and T.Takei, Retrieving. 2003, 3D shapes based on their appearance, ACM SIGMM Workshop on Multimedia Information Retrieval, Berkeley, California, pp. 39–46.
Index Terms

Computer Science
Information Sciences

Keywords

Geometry Compression Artificial Intelligent Genetic Algorithm Neural Network Multilayer feed forward